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Action following the discovery of a global association between the whole genome and adverse event risk in a clinical drug‐development programme
Author(s) -
Whitehead John,
Kelly Patrick,
Zhou Yinghui,
Stallard Nigel,
Thygesen Helene,
Bowman Clive
Publication year - 2008
Publication title -
pharmaceutical statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 38
eISSN - 1539-1612
pISSN - 1539-1604
DOI - 10.1002/pst.357
Subject(s) - adverse effect , medicine , event (particle physics) , association (psychology) , genetic association , risk analysis (engineering) , intensive care medicine , genotype , pharmacology , psychology , genetics , biology , single nucleotide polymorphism , gene , physics , quantum mechanics , psychotherapist
Observation of adverse drug reactions during drug development can cause closure of the whole programme. However, if association between the genotype and the risk of an adverse event is discovered, then it might suffice to exclude patients of certain genotypes from future recruitment. Various sequential and non‐sequential procedures are available to identify an association between the whole genome, or at least a portion of it, and the incidence of adverse events. In this paper we start with a suspected association between the genotype and the risk of an adverse event and suppose that the genetic subgroups with elevated risk can be identified. Our focus is determination of whether the patients identified as being at risk should be excluded from further studies of the drug. We propose using a utility function to determine the appropriate action, taking into account the relative costs of suffering an adverse reaction and of failing to alleviate the patient's disease. Two illustrative examples are presented, one comparing patients who suffer from an adverse event with contemporary patients who do not, and the other making use of a reference control group. We also illustrate two classification methods, LASSO and CART, for identifying patients at risk, but we stress that any appropriate classification method could be used in conjunction with the proposed utility function. Our emphasis is on determining the action to take rather than on providing definitive evidence of an association. Copyright © 2008 John Wiley & Sons, Ltd.

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